user
Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.

### Instruction:
Create a Random Forest classifier to predict the sentiment of a given sentence.

### Input:
The food here is really amazing.

### Response:
assistant
"""
Create a Random Forest classifier to predict the sentiment of a given sentence
"""

from sklearn.ensemble import RandomForestClassifier
import numpy as np 

# create the input for the classifier: 
sentence = np.array([[1,0,0,0,1]]) # represent the sentence as a vector of ones and zeros, 1 being positive and 0 being negative 

# define the label 
label = np.array([1]) # 1 being positive and 0 being negative 

# create and train theRandom Forest classifier 
clf = RandomForestClassifier() 
clf.fit(sentence, label) 

#test the classifier 
test_sentence = 'The food here is really amazing.'
test_sentence_vector = np.array([[1,0,0,0,1]]) 
prediction = clf.predict(test_sentence_vector) 

# output the sentiment prediction 
print(prediction)  # output: 1 (positive sentiment)